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- W1566266003 abstract "If the landscape of the objective function is unimodal, the efficiency of population-based optimization algorithms (POAs) can be improved by selecting strategies for local search around a best solution. If the landscape is multimodal, the robustness of the POAs can be improved by selecting strategies for global search in search space. We have proposed a method that estimates the landscape modality by sampling the objective values along a line and counting the number of changes in the objective values from increasing to decreasing and vice versa. In this study, in order to improve the performance of particle swarm optimization (PSO), we propose to select a proper strategy according to the landscape modality: The gbest model is selected in unimodal landscape and the lbest model is selected in multimodal landscape. The advantage of the proposed method is shown by solving unimodal and multimodal problems and by comparing it with standard PSOs." @default.
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- W1566266003 date "2014-07-14" @default.
- W1566266003 modified "2023-09-23" @default.
- W1566266003 title "Selecting Strategies in Particle Swarm Optimization by Sampling-Based Landscape Modality Detection" @default.
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